Main Definition
Omics Data refers to the large, complex datasets generated by genomics, proteomics, transcriptomics, metabolomics, and related life sciences fields typically produced by high-throughput sequencing and analysis instruments.
Omics datasets are notable for their sheer volume and their long-term research value, which often requires retention well beyond the active project.
Omics data presents a distinct management challenge. A single genome sequencing run can produce hundreds of gigabytes of FASTQ files. Multiply that across thousands of samples in a drug discovery pipeline or multi-site research collaboration, and the pipeline grows fast. These files move across parallel file systems, object stores, and archive tiers, often without consistent naming conventions or lifecycle policies. The problem can get even more complicated with multi-omics research, where teams combine datasets from different disciplines to build richer biological models. Research institutions, pharmaceutical companies, and healthcare organizations managing omics data at scale need visibility into data ownership, data movement, predictive analytics around storage capacity, and deep metadata extraction capabilities to ensure context for files and enable FAIR data-compliance.
Starfish helps life sciences teams manage omics data at scale across multiple teams. Starfish scans billions of files across heterogeneous storage, extracting metadata from 100+ file types (including FASTQ, BAM, and other genomics formats), automates workflow movement, and provides leaders with a single view of all their omics data.
Related Links
- Introduction to Omics | National Center for Biotechnology Information
- The Power of Multi-Omics | Frontline Genomics
- Starfish Storage for Life Sciences | Starfish Storage
- Starfish Storage automates dozens of scientific instrument workflows for a leading research hospital | Starfish Storage Blog
